Machine Learning with PyTorch

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6:49:12

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00001 0.0 Course Introduction.mp4

04:04

00002 0.1 Lesson Introductions.mp4

06:42

00003 0.2 Installing the lessons and platform.mp4

07:59

00004 Learning objectives.mp4

01:24

00005 1.1 Understand the course at a high level.mp4

05:27

00006 1.2 Describe the techniques used in machine learning.mp4

09:23

00007 1.3 Describe the libraries used in machine learning.mp4

08:21

00008 1.4 Understand the difference between deep learning and other ML techniques.mp4

09:43

00009 1.5 Utilize additional concepts in ML.mp4

27:05

00010 1.6 Understand the types of network layers and activation functions.mp4

16:43

00011 1.7 Understand metrics.mp4

13:34

00012 Learning objectives.mp4

01:04

00013 2.1 Perform a task in scikit-learn.mp4

11:18

00014 2.2 Perform a task in Keras with TensorFlow.mp4

16:37

00015 2.3 Perform a task in PyTorch.mp4

11:46

00016 2.4 Classify an image with PyTorch.mp4

05:19

00017 Learning objectives.mp4

01:17

00018 3.1 Use tensors autograd and NumPy interfaces.mp4

17:12

00019 3.2 Establish a low-level neural network.mp4

18:17

00020 3.3 Implement a neural network with torch.nn.mp4

08:09

00021 3.4 Understand why bias is important.mp4

04:11

00022 3.5 Identify other torch tools.mp4

02:08

00023 Learning objectives.mp4

02:33

00024 4.1 Create a simple feature classifier--Part 1.mp4

17:52

00025 4.2 Create a simple feature classifier--Part 2.mp4

19:14

00026 4.3 Create an image classifier.mp4

26:02

00027 4.4 Utilize regression prediction.mp4

22:28

00028 4.5 Do clustering with PyTorch.mp4

22:52

00029 4.6 Use generative adversarial networks--Part 1.mp4

17:25

00030 4.7 Use generative adversarial networks--Part 2.mp4

20:45

00031 4.8 Use a part of speech tagger.mp4

19:07

00032 Learning objectives.mp4

00:37

00033 5.1 Start with torchvision.models.mp4

15:05

00034 5.2 Retrain pretrained models.mp4

03:57

00035 5.3 Modify network layers.mp4

12:51

00036 Machine Learning with PyTorch - Summary.mp4

00:41

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